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strategy: improve harmonic by adding HMM filter to denoise shark signal
strategy: improve harmonic by adding HMM filter to denoise shark signal
This commit is contained in:
austin362667
Austin Liu
parent
b80ac89486
commit
c8aa4ae400
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@ -16,8 +16,8 @@ exchangeStrategies:
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harmonic:
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symbol: BTCBUSD
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interval: 1s
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window: 500
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quantity: 0.05
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window: 60
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quantity: 0.005
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# Draw pnl
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drawGraph: true
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graphPNLPath: "./pnl.png"
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@ -26,12 +26,12 @@ exchangeStrategies:
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backtest:
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sessions:
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- binance
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startTime: "2022-09-30"
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endTime: "2022-10-01"
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startTime: "2022-10-01"
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endTime: "2022-10-07"
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symbols:
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- BTCBUSD
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accounts:
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binance:
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balances:
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BTC: 1.0
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BUSD: 40_000.0
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BUSD: 60_000.0
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@ -3,14 +3,17 @@ package harmonic
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import (
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"context"
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"fmt"
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"os"
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"sync"
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"github.com/c9s/bbgo/pkg/bbgo"
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"github.com/c9s/bbgo/pkg/data/tsv"
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"github.com/c9s/bbgo/pkg/datatype/floats"
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"github.com/c9s/bbgo/pkg/fixedpoint"
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"github.com/c9s/bbgo/pkg/indicator"
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"github.com/c9s/bbgo/pkg/types"
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"github.com/sirupsen/logrus"
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floats2 "gonum.org/v1/gonum/floats"
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)
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const ID = "harmonic"
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@ -317,6 +320,7 @@ func (s *Strategy) Run(ctx context.Context, orderExecutor bbgo.OrderExecutor, se
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}
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})
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s.InitDrawCommands(&profitSlice, &cumProfitSlice)
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s.orderExecutor.TradeCollector().OnPositionUpdate(func(position *types.Position) {
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bbgo.Sync(ctx, s)
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})
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@ -332,66 +336,131 @@ func (s *Strategy) Run(ctx context.Context, orderExecutor bbgo.OrderExecutor, se
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if klines, ok := kLineStore.KLinesOfInterval(s.shark.Interval); ok {
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s.shark.LoadK((*klines)[0:])
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}
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states := types.NewQueue(s.Window)
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states.Update(0)
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s.session.MarketDataStream.OnKLineClosed(types.KLineWith(s.Symbol, s.Interval, func(kline types.KLine) {
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log.Infof("Shark Score: %f, Current Price: %f", s.shark.Last(), kline.Close.Float64())
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//previousRegime := s.shark.Values.Tail(10).Mean()
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//zeroThreshold := 5.
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nextState := alpha(s.shark.Array(s.Window), states.Array(s.Window), s.Window)
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states.Update(nextState)
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log.Infof("Denoised signal via HMM: %f", states.Last())
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if s.shark.Rank(s.Window).Last()/float64(s.Window) > 0.99 { // && ((previousRegime < zeroThreshold && previousRegime > -zeroThreshold) || s.shark.Index(1) < 0)
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if s.Position.IsShort() {
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_ = s.orderExecutor.GracefulCancel(ctx)
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s.orderExecutor.ClosePosition(ctx, fixedpoint.One, "close short position")
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if states.Length() < s.Window {
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return
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}
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_, err := s.orderExecutor.SubmitOrders(ctx, types.SubmitOrder{
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Symbol: s.Symbol,
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Side: types.SideTypeBuy,
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Quantity: s.Quantity,
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Type: types.OrderTypeMarket,
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Tag: "shark long: buy in",
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})
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if err == nil {
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_, err = s.orderExecutor.SubmitOrders(ctx, types.SubmitOrder{
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Symbol: s.Symbol,
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Side: types.SideTypeSell,
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Quantity: s.Quantity,
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Price: fixedpoint.NewFromFloat(s.shark.Highs.Tail(100).Max()),
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Type: types.OrderTypeLimit,
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Tag: "shark long: sell back",
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})
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}
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if err != nil {
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log.Errorln(err)
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}
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} else if s.shark.Rank(s.Window).Last()/float64(s.Window) < 0.01 { // && ((previousRegime < zeroThreshold && previousRegime > -zeroThreshold) || s.shark.Index(1) > 0)
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direction := 0.
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if s.Position.IsLong() {
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_ = s.orderExecutor.GracefulCancel(ctx)
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s.orderExecutor.ClosePosition(ctx, fixedpoint.One, "close long position")
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direction = 1.
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} else if s.Position.IsShort() {
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direction = -1.
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}
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_, err := s.orderExecutor.SubmitOrders(ctx, types.SubmitOrder{
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if s.Position.IsOpened(kline.Close) && states.Mean(5) == 0 {
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s.orderExecutor.ClosePosition(ctx, fixedpoint.One)
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}
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if states.Mean(5) == 1 && direction != 1 {
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_, _ = s.orderExecutor.SubmitOrders(ctx, types.SubmitOrder{
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Symbol: s.Symbol,
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Side: types.SideTypeBuy,
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Quantity: s.Quantity,
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Type: types.OrderTypeMarket,
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Tag: "shark long",
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})
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} else if states.Mean(5) == -1 && direction != -1 {
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_, _ = s.orderExecutor.SubmitOrders(ctx, types.SubmitOrder{
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Symbol: s.Symbol,
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Side: types.SideTypeSell,
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Quantity: s.Quantity,
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Type: types.OrderTypeMarket,
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Tag: "shark short: sell in",
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Tag: "shark short",
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})
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if err == nil {
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_, err = s.orderExecutor.SubmitOrders(ctx, types.SubmitOrder{
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Symbol: s.Symbol,
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Side: types.SideTypeBuy,
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Quantity: s.Quantity,
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Price: fixedpoint.NewFromFloat(s.shark.Lows.Tail(100).Min()),
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Type: types.OrderTypeLimit,
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Tag: "shark short: buy back",
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})
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}
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if err != nil {
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log.Errorln(err)
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}
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}
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}))
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bbgo.OnShutdown(ctx, func(ctx context.Context, wg *sync.WaitGroup) {
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defer wg.Done()
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// Output accumulated profit report
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if bbgo.IsBackTesting {
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defer s.AccumulatedProfitReport.Output(s.Symbol)
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if s.DrawGraph {
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if err := s.Draw(&profitSlice, &cumProfitSlice); err != nil {
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log.WithError(err).Errorf("cannot draw graph")
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}
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}
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}
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_, _ = fmt.Fprintln(os.Stderr, s.TradeStats.String())
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_ = s.orderExecutor.GracefulCancel(ctx)
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})
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return nil
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}
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// TODO: dirichlet distribution is a too naive solution
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func observationDistribution(y_t, x_t float64) float64 {
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if x_t == 0. && y_t == 0 {
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// observed zero value from indicator when in neutral state
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return 1.
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} else if x_t > 0. && y_t > 0. {
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// observed positive value from indicator when in long state
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return 1.
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} else if x_t < 0. && y_t < 0. {
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// observed negative value from indicator when in short state
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return 1.
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} else {
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return 0.
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}
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}
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func transitionProbability(x_t0, x_t1 int) float64 {
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// stick to the same sate
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if x_t0 == x_t1 {
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return 0.99
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}
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// transit to next new state
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return 1 - 0.99
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}
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func alpha(y_t []float64, x_t []float64, l int) float64 {
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al := make([]float64, l)
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an := make([]float64, l)
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as := make([]float64, l)
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long := 0.
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neut := 0.
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short := 0.
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// n is the incremental time steps
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for n := 2; n <= len(x_t); n++ {
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for j := -1; j <= 1; j++ {
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sil := make([]float64, 3)
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sin := make([]float64, 3)
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sis := make([]float64, 3)
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for i := -1; i <= 1; i++ {
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sil = append(sil, x_t[n-1-1]*transitionProbability(i, j))
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sin = append(sin, x_t[n-1-1]*transitionProbability(i, j))
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sis = append(sis, x_t[n-1-1]*transitionProbability(i, j))
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}
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if j > 0 {
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long = floats2.Max(sil) * observationDistribution(y_t[n-1], float64(j))
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al = append(al, long)
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} else if j == 0 {
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neut = floats2.Max(sin) * observationDistribution(y_t[n-1], float64(j))
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an = append(an, neut)
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} else if j < 0 {
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short = floats2.Max(sis) * observationDistribution(y_t[n-1], float64(j))
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as = append(as, short)
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}
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}
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}
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maximum := floats2.Max([]float64{long, neut, short})
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if maximum == long {
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return 1
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} else if maximum == short {
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return -1
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}
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return 0
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}
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